Ching-pei Lee

activity

20152026

most citedA Distributed Quasi-Newton Algorithm for Primal and Dual Regularized Empirical Risk Minimization

1 citations · 1 across the 6 of their papers we have counts for

collaborators

Showing 2018Show all

4 papers · 1 filter

math.OC2018

First-order algorithms converge faster than $O (1/ k)$ on convex problems

Ching-pei Lee, Stephen J. Wright

It is well known that both gradient descent and stochastic coordinate descent achieve a global convergence rate of $O (1/ k)$ in the objective value, when applied to a scheme for min…

math.OC2018

Inexact Variable Metric Stochastic Block-Coordinate Descent for Regularized Optimization

Ching-pei Lee, Stephen J. Wright

Block-coordinate descent (BCD) is a popular framework for large-scale regularized optimization problems with block-separable structure. Existing methods have several limitations. T…

math.OC2018

A Distributed Quasi-Newton Algorithm for Empirical Risk Minimization with Nonsmooth Regularization

Ching-pei Lee, Cong Han Lim, Stephen J. Wright

We propose a communication- and computation-efficient distributed optimization algorithm using second-order information for solving ERM problems with a nonsmooth regularization ter…

math.OC2018

Inexact Successive Quadratic Approximation for Regularized Optimization

Ching-pei Lee, Stephen J. Wright

Successive quadratic approximations, or second-order proximal methods, are useful for minimizing functions that are a sum of a smooth part and a convex, possibly nonsmooth part tha…

First-order algorithms converge faster than O(1/k) on convex problems

Inexact Variable Metric Stochastic Block-Coordinate Descent for Regularized Optimization

A Distributed Quasi-Newton Algorithm for Empirical Risk Minimization with Nonsmooth Regularization

Inexact Successive Quadratic Approximation for Regularized Optimization

First-order algorithms converge faster than $O (1/ k)$ on convex problems